zoukankan      html  css  js  c++  java
  • Leetcode-Minimum Window Substring

    Given a string S and a string T, find the minimum window in S which will contain all the characters in T in complexity O(n).

    For example,
    S = "ADOBECODEBANC"
    T = "ABC"

    Minimum window is "BANC".

    Note:
    If there is no such window in S that covers all characters in T, return the emtpy string "".

    If there are multiple such windows, you are guaranteed that there will always be only one unique minimum window in S.

    Analysis:

    We use a HashMap to store the number of each char in T. We scan the string S from 0 to its end. For each char, if it is one of the char in T, we decrease the count of this char in the Map. If the count of the char is smaller than 0, it means that at current position, the number of this char is more than needed. We also record the position of each char in S that belongs to T. Everytime a char is enqueued, we check the head of the queue. If the char of the head is more than needed, we then dequeue the head and check the next head until the number of the char of the head is less than or equal to 0.

    Solution:

     1 public class Solution {
     2     public String minWindow(String S, String T) {
     3         if (S.length()==0 || T.length()==0) return "";
     4         
     5         Map<Character,Integer> mapT = new HashMap<Character,Integer>();
     6         for (int i=0;i<T.length();i++){
     7             char c = T.charAt(i);
     8             if (mapT.containsKey(c))
     9                 mapT.put(c,mapT.get(c)+1);
    10             else mapT.put(c,1);
    11         }
    12 
    13         List<Integer> indexList = new LinkedList<Integer>();
    14         int left = T.length();
    15         int start = -1, end = -1;
    16         int curLen = Integer.MAX_VALUE;
    17         for (int i=0;i<S.length();i++){
    18             char c = S.charAt(i);
    19             if (!mapT.containsKey(c)) continue;
    20 
    21             int num = mapT.get(c);
    22             if (num>0) left--;
    23             mapT.put(c,num-1);
    24             indexList.add(i);
    25 
    26             char head = S.charAt(indexList.get(0));
    27             while (mapT.get(head)<0){
    28                 indexList.remove(0);
    29                 mapT.put(head,mapT.get(head)+1);
    30                 head = S.charAt(indexList.get(0));
    31             }
    32 
    33             if (left==0){
    34                 int newLen = indexList.get(indexList.size()-1)-indexList.get(0)+1;
    35                 if (newLen<curLen){
    36                     start = indexList.get(0);
    37                     end = indexList.get(indexList.size()-1);
    38                     curLen = newLen;
    39                 }
    40              }
    41          }
    42 
    43          if (curLen==Integer.MAX_VALUE) return "";
    44          else {
    45              String res = S.substring(start,end+1);
    46              return res;       
    47          }
    48     }
    49 }

    NOTE: I used ArrayList at the begnning and got TLE error. After changing to LinkedList, the solution is accepted. Because:

    LinkedList is FASTER when perform DELETE and INSERT operation.

    ArrayList is FASTER when perform QUERY operation, i.e., check the element on position n.

  • 相关阅读:
    redis使用lua脚本遇到的问题
    redis使用scan count 返回数量不准确
    window系统下搭建本地的NuGet Server
    windows10使用docker发布.netcore程序
    windows10使用docker安装mysql
    windows10搭建redis4.0集群
    windows10配置redis主从复制
    windows10安装redis4.0
    mysql 共享排他锁
    mysql drop表以后恢复数据
  • 原文地址:https://www.cnblogs.com/lishiblog/p/4117881.html
Copyright © 2011-2022 走看看